Continued from Part 01 . . . One of the things lenders are looking for is liquidity. How much cash-equivalency does the borrower have? Something always comes up. Does the borrower have enough liquidity to get through it? Cash equivalents include things like savings and checking accounts, retirement funds, cash value of life insurance policies, and stock / bond portfolios. 

The preferred liquidity threshold is currently hovering around 10% of the requested loan amount. For example, a $3.5 million loan would require the borrower to have proof of $350,000 in liquid funds remaining after the close of escrow, whether the escrow is for purchase or refinance  

That is a high hurdle. A $3.5 million loan may be secured by a well-located 12 or 15 unit property. Not many folks with buildings that size have $350,000 in cash. Nonetheless, a liquidity problem, which may be temporary, is easier to manage than a poor location (which is permanent).

Nobody reading this article needs guidance on real estate investing. When about half of America has zero net worth or less (i.e., debts exceed assets), the person owning rental property is already ahead. But an awful lot of good apartment owners are not liquid. They have made fine money in real estate but most of it is in equity appreciation, not liquid cash flow. Now, however, having substantial liquidity is required for the borrower to get the best loans.

Cash is self-explanatory. It is maximally liquid (good) but subject to erosion from inflation (bad). One way to manage cash assets is by having a necessary minimum for emergencies, but not enough that the loss from inflation is crippling. One reads about portfolios with 10-20% cash, often invested in short term Treasury bills (bills: mature in less than one year) or possibly T-notes (notes: 1 -10 year maturities). When rates go up the shorter terms can be desirable because the potential for reinvesting at higher rates is present.

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Once an appropriate amount of emergency savings are accumulated, the rest could be geared towards stocks or bonds (or both). The hope is that the liquid portfolio will grow at least as fast as income property values, and sometimes this happens. Two things that would be important to note in a perspective portfolio would be the Compound Annual Rate of Growth (CAGR) and the Standard Deviation (SD), which indicates risk. Most folks (but not all: people are different) would probably want a portfolio that provides the highest CAGR with the lowest SD. We’ll talk about that next month.

Single (Anything) Risk  

William Bernstein was trained as a neurologist and became a self-taught financial theorist with a concentration in portfolio theory. He advocates owning asset classes rather than individual stocks or bonds. Diversifying assets by asset class serves to reduce both single-stock risk and single-industry risk.

Single Stock Risk  

An example of single-stock risk might be General Electric (GE), which was a member of the Dow 30 Industrial Average or 111 years (1907 to 2018). It was not generally considered a risky stock . . . but it became so in recent years. Its price on Jul 7, 2000 was $51.31. Three months later, on Oct 6, 2000, it had advanced to $56.38. That is a 39% gain (annualized). It hasn’t been that high since. On Jan 24, 2003 it was $23.06. It dropped more than 50% in two years and three months. Some stocks drop faster. Some drop further. Some pause, and then continue their slow decline. GE was in the latter group. On May 17, 2019, General Electric shares were offered at $10 each. GE was one of the companies affected by the collapse (2000-2002), and while it technically survived, the company has not yet recovered. The investors who kept their stock saw it drop from $56 to $10 (a loss of 82%) in 19 years: single-stock risk, indeed!

Single Index Risk: Real Estate vs. Emerging Market 

The Callan Periodic Table of Investment Returns (1999 – 2018) presents a sense of single-industry risk ( The grid shows the annual returns of 9 industries over 18 years [the Emerging Market index was added in 2001 (two years later), bringing the current Callan Table to 20 years]. During the period from 2001 to 2018 the Real Estate (think: REITs) and Emerging Market indices each appeared multiple times as the top returning index. The average annual return of the Real Estate index from 2001 to 2018 was 7.67%. In other words, $100 invested would have grown to $379.41.  A similar $100 investment in the Emerging Market index would have an ending value of $162.59.

In both cases it is useful to remember that the first $100 of ending value was not profit. It was simply getting one’s own money back. Technically, this is referred to as the return of the investment. The gain after getting one’s own money back is the return on the investment


During the period 1999 – 2018, the Real Estate index ranged from plus 42.12% (2006) to minus 48.21% (2008). The Emerging Markets index went from plus 55.82% (2003) to a minus 53.33% (2008). 

Interesting lessons can be drawn from this data. Both single-stock risk (example: GE) and single-industry risk (example: Real Estate or Emerging Markets indices) can be debilitating. The reader will notice that the Real Estate index stretched over 90 percentage points (plus 42.12% to minus 48.21%). The Emerging Market index was even more volatile: a touch over 109 percentage points.

Broad Market Indices  

Broad market indices show themselves to be less volatile, possibly because each index contains a number of stocks and the recovering stocks help to support the index. Notwithstanding the fact that the stock market as a whole has made exceptional gains in some years and absorbed shocking losses in others, since 1957 (it was higher before that date) the S&P 500 (a broad market index of the 500 largest exchange-listed companies) reflects a compounded 8% average return. Being well diversified doesn’t stop the indices from dropping, but it may help them to not stay low forever. That 8% from the S&P 500 is a return roughly equivalent to the Real Estate index, which (vide supra) came in a 7.67%. We are talking about diversification, not yield, but just to illustrate that an annualized 8% return is not insignificant consider that at an 8% growth level money will double about every nine years (Rule of 72), or five doublings in a 45 year working career. Hypothetically, a parent (or grandparent) could make a down payment and buy a house for her child on the day he’s born. Let the tenants pay it off. Sell it when he’s ready for college and throw the net sum (for illustrative purposes, estimated at $400,000) into the market at 8%. Five doublings later now adult child’s retirement account has grown to $12,800,000. The math is as follows: $400,000 to $800,000 is one doubling. The next comes to $1,600,000. Then, $3,200,000. The fourth nine year doubling is $6,400,000. The last doubling comes to $12,800,000. (This number assumes no ex-wives.) 

A Bit on Diversification

Bernstein (The Intelligent Asset Allocator) has a wonderfully simple example of why diversification works: it reduces the possibility of loss.

Example: You flip a coin once a year. If it’s heads, your rich Uncle Fred will guarantee your retirement account returns 30% for that year. If it’s tails, then your account must absorb a 10% loss for the year.

Undiversified Coin Flip

In a coin flip, there are only two options: heads or tails. Over a sufficient number of trials, the results of a coin toss approach 50/50. But the fact that one result yields a 30% return and the other a (minus) 10% changes the win / loss calculus. 

The coin flip still happens annually, at the end of the year. If its heads, you keep your accumulated retirement funds and Uncle Fred gives you a 30% bonus. Keeping the original sum and gaining 30% can be expressed mathematically as 1.3. You stroll out Uncle Fred’s door with 130% of what you entered with. 

If the coin is a tail, 10% of your retirement funds go to Uncle Fred. You started with 100% of your retirement funds, lost 10%, and now have 90% left. This can be expressed as 0.9.

A cycle of one head at the end of the first year and one tail at the end of the second would take two years to complete. The first year, in this example, the math is 1.3 (for the gain on the head). In the other year the math is 0.9 (for the loss on the tail). The formula for a two year hold would be 1.3 x 0.9 = 1.17. You leave the second year with all your original funds plus a 17% profit. The gain is 8.5% per year.

Diversified Coin Flip

Time goes by.  Uncle Fred offers to divide your retirement account into two equal parts (Part A and Part B) and conduct a separate coin toss for each half. Whether heads or tails, the results of each coin toss for Part A will be limited to one half of the (former) portfolio.

When the coin for Part B is flipped it, too, will come up either heads or tails. This constitutes the gain or loss on the other half of the original portfolio. If you accept Uncle Fred’s offer, you will have two uncorrelated portfolios. Whatever happens when the coin is flipped for Part A has no effect on Part B.

Now, the math changes slightly. Instead of having, for example, one $100 retirement account with two possibilities (heads or tails), we now have two $50 accounts with four possibilities (see chart, below).

Flipping a head for Part A still yields a 30% gain, but only for the “A” half of the portfolio. Similarly, a tails results in a minus 10% return, but – again – only for the “A” half. So the math for Part A would be thus:

Heads would return +$15 (30% of $50). Tails would return -$5 (10% of $50). Combined, this example would result in a gain of $10 (+$15 and -$5) for that half of the portfolio.

Then the process is repeated with Part B. The sum of gains and / or losses on Part A and Part B constitutes the total portfolio return.

The effect of diversifying the one coin-toss portfolio into two will be to have four prospective results. Each of the four possibilities is equally likely.




Since each of the four possible outcomes is equally likely, and in a representative four-year period you will have one of each outcome, you find that your account will increase by a factor of: 1.3 x 1.1 x 1.1 x .9 = 1.4157.

Bernstein writes,
“Outcomes 1 and 4 are the same as they would be in a single  coin toss, with the original returns of +30% and -10%, respectively. However, there are two additional possible outcomes, in which the two tosses result in one head and one tail. The total return in these cases is 10% (one half of +30% plus one-half of -10%).

Being handy with numbers, you calculate that your annualized return for this two-coin-toss sequence is . . . . [about 9%] . . . which is nearly a half percentage point higher than your previous expected return of [about 8.5%] with only one coin toss. Even more amazingly, you realize that your risk has been reduced.” With the single coin toss there were only two possibilities: you were either going to win 30% or lose 10%. Over a long enough period of time, half of the throws would result in a loss for you. That’s a 50% loss ratio. With two separate coin tosses [one for Part A and another for Part B], there are four possibilities, only one of which results in a loss: a 25% loss ratio. Bernstein continues, “Wise old Uncle Fred has introduced you to the most important concept in portfolio theory:” 

 This article is for informational purposes only and is not intended as professional advice. For specific circumstances, please contact an appropriately licensed professional. Klarise Yahya is a Commercial Mortgage Broker specializing in difficult-to-place mortgages for any kind of property. If you are thinking of refinancing or purchasing real estate Klarise Yahya can help. For a complimentary mortgage analysis, please call her at (818) 414-7830 or email [email protected].